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Displaying posts with tag: aws (reset)
Percona Support with Amazon RDS

This blog post will give a brief overview of Amazon RDS capabilities and limitations, and how Percona Support can help you succeed in your Amazon RDS deployments.

One of the common questions that we get from customers and prospective customers is about Percona Support with Amazon RDS. As many companies have shifted to the cloud, or are considering how to do so, it’s natural to try to understand the limitations inherent in different deployment strategies.

Why Use Amazon RDS?

As more companies move to using the cloud, we’ve seen a shift towards work models in technical teams that require software developers to take on more operational duties than they have traditionally. This makes it essential to abstract infrastructure so it can be interacted with as code, whether through automation or APIs. Amazon RDS presents a compelling DBaaS product with significant flexibility while maintaining ease of deployment.

Use …

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How to Configure Aurora RDS Parameters

In this blog post, we’ll look at some tips on how to configure Aurora RDS parameters.

I was recently deploying a few Aurora RDS instances, a process very similar to configuring a regular RDS instance. I noticed a few minor differences in the way you configure Aurora RDS parameters, and very few articles on how the commands should be structured (for RDS as well as Aurora). The only real literature available is the official Amazon RDS documentation.

This blog provides a concise “how-to” guide to quickly change Aurora RDS parameters using the AWS CLI. Aurora retains the parameter group model introduced with RDS, with new instances having the default read only parameter groups. For a new instance, you need to create and allocate a new parameter group (this requires a DB reboot). After that, you can apply changes to …

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How we use ProxySQL Tools

When we started working with a customer they asked us to setup for them more reliable and performant MySQL database. At the time they were using Percona XtraDB cluster with ELB to balance read traffic between PXC nodes. There was no writer redundancy – if a writer node was down, the app was down. The app by the way is a Magento backed online shop. All stuff was running in AWS.

We started to design the new database architecture. The first component we threw away was ELB. A simple OLTP sysbench test showed that ELB was a bottleneck. The ELB was capable to deliver somewhat around 6800 qps while with ProxySQL the Percona XtraDB Cluster was a bottleneck. We squeezed 10k qps from ProxySQL + PXC. That basically means we got all ProxySQL feature free of charge.

But one ProxySQL instance is a SPOF. To make ProxySQL highly available we put another instance and managed it with keepalived.

Eventually the architecture looked like …

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Best practices for migrating databases to Amazon Aurora

If you like to read (a lot) and you're considering to migrate your database workloads to AWS, this might be something for you. Nearly 75 pages of ideas for planning, executing, and troubleshooting database migrations to Amazon Aurora.

I recently published an Aurora Migration Handbook in the form of an AWS Whitepaper. The document can be downloaded from here:

https://d0.awsstatic.com/whitepapers/Migration/amazon-aurora-migration-handbook.pdf

Happy reading!

Setup high availability for ProxySQL via KeepAlived in AWS

Usually application do not connect directly to Percona XtraDB Cluster, but go through a proxy – ProxySQL, for instance. However if only one proxy node is used it becomes a single point of failure. Not long ago Marco Tusa wrote about how to configure two ProxySQL nodes in front of XtraDB cluster. If deployed on EC2 instances it doesn’t work that way because Amazon doesn’t allow to assign secondary IP address on an interface.

This post describes how to configure highly available ProxySQL with keepalived, proxysql-tools and AWS Elastic Network Interface(ENI).
The application connects to a single Virtual IP. The VIP is assigned to ENI which is managed by keepalived. proxysql-tools moves ENI between …

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From Percona Live 2017: Thank You, Attendees!

From everyone at Percona and Percona Live 2017, we’d like to send a big thank you to all our sponsors, exhibitors, and attendees at this year’s conference.

This year’s conference was an outstanding success! The event brought the open source database community together, with a technical emphasis on the core topics of MySQL, MariaDB, MongoDB, PostgreSQL, AWS, RocksDB, time series, monitoring and other open source database technologies.

We will be posting tutorial and session presentation slides at the Percona Live site, and all of them should be available shortly. 

Highlights This Year:

  • Informative tutorials on day one, including …
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Percona Live 2017: Lessons Learned While Automating MySQL Deployments in the AWS Cloud

The last day of Percona Live 2017 is still going strong, with talks all the way until 4:00 pm (and closing remarks and a prize giveaway on the main stage then). I’m going to a few more sessions today, including one from Stephane Combaudon from Slice Technologies: Lessons learned while automating MySQL deployments in the AWS Cloud.

In this talk, Stephane discussed how automating deployments is a key success factor in the cloud. It is actually a great way to leverage the flexibility of the cloud. But often while automation is not too difficult for application code, it is much harder for databases. When Slice started automating their MySQL servers at Slice, they chose simple and production-proven …

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Monitoring Amazon RDS: Beyond Raw Logs

Amazon Relational Database Service (RDS) is a hosted database service in the AWS cloud. If your organization’s data is stored in one of the popular database systems, but on a company server or perhaps you’re renting a dedicated server, you might want to consider switching to Amazon RDS.  With Amazon RDS, you can choose from several relational database systems:  MySQL, MariaDB, Oracle, Postgres, and SQL Server, as well as Amazon Aurora.

There are many advantages to Amazon RDS, such as server scaling and load balancing of user traffic. Best of all, it can reduce the operational costs of running database software like MySQL. With Amazon RDS, you don’t need to worry about performing security updates, patching the operating system, or tuning the database. In fact, some of the patches Amazon deploys for MySQL and MariaDB are specifically designed to get better performance in a cloud setting.  Let’s look at some major …

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MySQL, –i-am-a-dummy!

In this blog post, we’ll look at how “operator error” can cause serious problems (like the one we saw last week with AWS), and how to avoid them in MySQL using

--i-am-a-dummy

.

Recently, AWS had some serious downtime in their East region, which they explained as the consequence of a bad deployment. It seems like most of the Internet was affected in one way or another. Some on Twitter dubbed it “S3 Dependency Awareness Day.”

Since the outage, many companies (especially Amazon!) are reviewing their production access and deployment procedures. It would be a lie if I claimed I’ve never made a mistake in production. In fact, I would be afraid of working with someone who claims to have never made a mistake in a production environment.

Making a mistake or two is how you learn to have a full …

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How to expand a striped LVM database volume in Amazon AWS without downtime

This procedure can be used to expand an LVM  database volume on Amazon AWS (but also apply to any storage area network environment equally). Let me start with this assumption: when you create volumes for database use in AWS using EBS, you stripe data across them in order to enhance performance.  If you aren't doing this... well, you should :-) Under this assumption, when you need to add more disk space to an existing database volume, you can't just add the disk(s) to the volume, as this would make the added space non striped, and would eventually create hotspots in the dataset. The correct approach in this situation is to create a number of new EBS disks enough to contain entire dataset plus the desired added space,so that you can grow the existing dataset while re-striping properly.
To make this clear, let's suppose you have a dataset volume of  3 TB,  made of 3 1TB EBS volumes which are striped across, but space is running …

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